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WiderPerson

A Diverse Dataset for Dense Pedestrian Detection in the Wild

WiderPerson

The WiderPerson dataset is a pedestrian detection benchmark dataset in the wild, of which images are selected from a wide range of scenarios, no longer limited to the traffic scenario. We choose 13,382 images and label about 400K annotations with various kinds of occlusions. We randomly select 8000/1000/4382 images as training, validation and testing subsets. Similar to CityPersons and WIDER FACE datasets, we do not release the bounding box ground truths for the test images. Users are required to submit final prediction files, which we shall proceed to evaluate.

WiderPerson
400000
Items
Classes
13382
Labels
Models using this dataset
Last updated on 
January 5, 2022
Licensed under 
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